On-line signature verification with hidden Markov models

J.G.A. Dolfing, E.H.L. Aarts, J.J.G.M. Oosterhout van

Research output: Other contribution

Abstract

This paper addresses the problem of online signature verification based on hidden Markov models (HMM). We use a novel type of digitizer tablet and pay special attention to the use of pen-tilt. We investigate the verification reliability based on different forgery types. We compare the discriminative value of the different features based on a linear discriminant analysis (LDA) and show that pen-tilt is important. On the basis of home-improved, over-the-shoulder and professional forgeries, we show that the amount of dynamic information available to an imposter is important and that forgeries based on paper copies are easier to detect. The results obtained with a database of almost 5000 signatures of 51 persons with highly skilled forgeries include equal-error rates between 1% and 1.9%.
Original languageEnglish
PublisherInstitute of Electrical and Electronics Engineers ( IEEE )
Number of pages4
Place of PublicationPiscataway
ISBN (Print)0-8186-8512-3
DOIs
Publication statusPublished - 1998
Externally publishedYes

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Hidden Markov models
Discriminant analysis

Cite this

Dolfing, J. G. A., Aarts, E. H. L., & Oosterhout van, J. J. G. M. (1998). On-line signature verification with hidden Markov models. Piscataway: Institute of Electrical and Electronics Engineers ( IEEE ). https://doi.org/10.1109/ICPR.1998.711942
Dolfing, J.G.A. ; Aarts, E.H.L. ; Oosterhout van, J.J.G.M. / On-line signature verification with hidden Markov models. 1998. Piscataway : Institute of Electrical and Electronics Engineers ( IEEE ). 4 p.
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abstract = "This paper addresses the problem of online signature verification based on hidden Markov models (HMM). We use a novel type of digitizer tablet and pay special attention to the use of pen-tilt. We investigate the verification reliability based on different forgery types. We compare the discriminative value of the different features based on a linear discriminant analysis (LDA) and show that pen-tilt is important. On the basis of home-improved, over-the-shoulder and professional forgeries, we show that the amount of dynamic information available to an imposter is important and that forgeries based on paper copies are easier to detect. The results obtained with a database of almost 5000 signatures of 51 persons with highly skilled forgeries include equal-error rates between 1{\%} and 1.9{\%}.",
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Dolfing, JGA, Aarts, EHL & Oosterhout van, JJGM 1998, On-line signature verification with hidden Markov models. Institute of Electrical and Electronics Engineers ( IEEE ), Piscataway. https://doi.org/10.1109/ICPR.1998.711942

On-line signature verification with hidden Markov models. / Dolfing, J.G.A.; Aarts, E.H.L.; Oosterhout van, J.J.G.M.

4 p. Piscataway : Institute of Electrical and Electronics Engineers ( IEEE ). 1998, .

Research output: Other contribution

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